This application pertains generally to digital signal processing, and in particular to the processing of detected radio signals emitted in the audio frequency bands. Specifically, this invention pertains to an algorithm which analyzes unintentional emissions from audio frequency platforms using push-to-talk transmitters and identifies the emitting platforms.
Intercepted audio band transmissions from unknown sources frequently contain modulations other than those associated with voice. These modulations can be generated by propulsion systems, transmitters, heating and cooling equipment, or other systems associated with the transmitting platform, and are unintentional. Such unintentional modulations can permit platform identification when properly detected, analyzed, and interpreted.
Various governmental and industrial organizations have signal collection activities which gather massive amounts of voice channel data. This data is or is not of interest, depending on the information contained in the voice signal and any additional information that might be gleaned from the channel itself. Additional data from unintentional modulations can be used to assist in culling uninteresting data and as a means of providing "external" cues to the identity or location of the transmitting device. Such information is of value in search and rescue missions. Exploring possible analysis techniques for exploiting unintentional modulations is a continuing activity of these organizations.
Some of these organizations are interested in the use of passive devices to detect, select, and identify signal sources of interest. Since the activities of the signal sources frequently are accompanied by radio transmissions, it was deemed possible to identify the emitting platform by detecting and identifying unintentional modulations imposed on the transmission. In addition, classifying emitters based on unintentional modulations can enhance the correlation of identification data from other, usually known reliable, sources.